美式看跌期权定价中的小波方法

本文采用有限差分格式和 Daubechies正交小波 ,提出了一种求解 Black- Scholes方程数值解新算法 .为美式看跌期定价提供了一条新的途径 .利用小波基的自适应性和消失矩特性 ,使偏微分算子矩阵和小波级数稀疏化 ,大大减少了计算量 .     

正交小波包及其在数字信号压缩中的应用

正交小波包是正交多分辨分析构造正交小波思想的自然延伸,正交小波包变换可以进一步分割小波空间,解决小波变换“高频低分辨”的问题,为数字信号处理提供获得高频高分辨效果的分析工具。最后,将小波包分析用于数字信号压缩问题的研究,获得了很好的变换压缩效果     

有限区间上的连续多小波

给出了用直线上的连续正交多小波构造有限区间上的多小波的一种方法.这种有限区间上的连续正交多小波可方便地用于解决有限区间上的问题(如图像压缩,解积分方程等).     

一种新的双正交小波的构造方法研究

在二进提升方案相关理论的基础上,结合双正交性、消失矩性和对称性条件,提出一种构造提升双正交小波的新方法.此方法从二进小波出发,考虑小波所具有的特性,通过选取适当的提升参数,具体构造了具有紧支撑、对称性、高阶消失矩和速降性的提升双正交小波.     

不同尺度下多项式滤波器的优化算法

１　　引　言 在小波分析的应用中,紧支撑正交对称的小波是非常可贵的．尤其是对称性,它在实际应用中具有非常重要的意义．但Daubechies的具有紧支撑正交小波无任何对称性和反对称性（除Haar小波外）．为了克服这一不足,崔锦泰和王建忠［１］提出了样条小波,样条小波用失去正交性换来了小波的对称性．A.Cohen［２］等引入了双正交小波似乎解决了这一问题,但它需要两个对偶的小波．匡正［３］等采用了小波的分式滤波器构造出了既正交又对称的小波,但却没有有限的支撑区间．本文欲采用优化的方法给出了一种构造具有任意正则性的多项式…     

与多通道正交小波滤波器相关的矩阵扩充的通解

本文研究了一类与多通道正交小波滤波器相关的矩阵方程。运用多相位分解的方法，获得了这类矩阵方程的通解。借助于该结果，可以从一组多通道正交小波能够产生许多组多通道正交小波。     

一类向量值正交小波的设计与性质

引入整数因子伸缩的向量值正交小波与向量值小波包的概念.运用仿酉向量滤波器理论和矩阵理论,给出具有整数因子伸缩的向量值正交小波存在的充要条件.提供了紧支撑向量值正交的构建算法,给出了相应的构建算例.利用时频分析方法与算子理论,刻画了一类向量值正交小波包的性质,得到了整数伸缩的向量值小波包的正交公式.     

三元双正交小波滤波器的刻画

研究由三元双正交插值尺度函数构造对应的双正交小波滤波器的矩阵扩充问题.当给定的一对三元双正交尺度函数中有一个为插值函数时,利用提升思想与矩阵多相分解方法,给出一类三元双正交小波滤波器的显示构造公式和一个计算实例.讨论了三元双正交小波包的的性质.     

L~2(R~n)上的半正交多小波框架

本文研究L2(Rn)上伸缩矩阵A满足|detA|1的半正交多小波框架.本文得到半正交和严格半正交框架的一系列性质及刻画.本文证明半正交Parseval多小波框架与广义多分辨分析(GMRA)Parseval多小波框架是等价的.特别地,本文利用最小频率支撑(MSF)多小波框架和小波集,构造若干半正交多小波框架的例子.     

小波的传递函数构造法

本从小波与尺度函数的传递函数出发,给出了构造小波母函数及尺度函数的构造方法,根据此方法,首先以小波与其尺度函数的传递函数为起点,构造了一个非正交小波,随后以此小波和一个已有的非正交步波为基准,进一步推广得到了一类非正交小波及尺度函数类,在非正交小波的基础上,利用将尺度函数正交化的方法,构造出了相应正交小波的函数值。     

On MRA Riesz wavelets

We investigate the properties of univariate MRA Riesz wavelets. In particular we obtain a generalization to semiorthogonal MRA wavelets of a well-known representation theorem for orthonormal MRA wavelets.

     

Φ~n空间中有界域上一种积分表示

本文应用单位分解的观点及积分表示中核函数的构造理论,得到~n空间中有界域上积分表示的一种抽象的一般形式,根据这种一般形式,可以得到至今许多区域上光滑函数和全纯函数种种已有的抽象公式和具体的积分公式。     

Cn空间中有界域上一种积分表示

本文应用单位分解的观点及积分表示中核函数的构造理论,得到Cⁿ空间中有界域上积分表示的一种抽象的一般形式,根据这种一般形式,可以得到至今许多区域上光滑函数和全纯函数种种已有的抽象公式和具体的积分公式。     

How to Get the Original Discrete Approximation for the Pyramid Algorithm of Multiresolution Decomposition

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Directional Haar wavelet frames on triangles

Traditional wavelets are not very effective in dealing with images that contain orientated discontinuities (edges). To achieve a more efficient representation one has to use basis elements with much higher directional sensitivity. In recent years several approaches like curvelets and shearlets have been studied providing essentially optimal approximation properties for images that are piecewise smooth and have discontinuities along C²-curves. While curvelets and shearlets have compact support in frequency domain, we construct directional wavelet frames generated by functions with compact support in time domain. Our Haar wavelet constructions can be seen as special composite dilation wavelets, being based on a generalized multiresolution analysis (MRA) associated with a dilation matrix and a finite collection of ‘shear’ matrices. The complete system of constructed wavelet functions forms a Parseval frame. Based on this MRA structure we provide an efficient filter bank algorithm. The freedom obtained by the redundancy of the applied Haar functions will be used for an efficient sparse representation of piecewise constant images as well as for image denoising.     

Wavelet bases in generalized Besov spaces

In this paper we obtain a wavelet representation in (inhomogeneous) Besov spaces of generalized smoothness via interpolation techniques. As consequence, we show that compactly supported wavelets of Daubechies type provide an unconditional Schauder basis in these spaces when the integrability parameters are finite.     

Circulant Wavelet Preconditioners for Solving Elliptic Differential Equations and Boundary Integral Equations

In this paper is discussed solving an elliptic equation and a boundary integral equation of the second kind by representation of compactly supported wavelets. By using wavelet bases and the Galerkin method for these equations, we obtain a stiff sparse matrix that can be ill-conditioned. Therefore, we have to introduce an operator which maps every sparse matrix to a circulant sparse matrix. This class of circulant matrices is a class of preconditioners in a Banach space. Based on having some properties in the spectral theory for this class of matrices, we conclude that the circulant matrices are a good class of preconditioners for solving these equations. We called them circulant wavelet preconditioners (CWP). Therefore, a class of algorithms is introduced for rapid numerical application.     

Directional Wavelet Bases Constructions with Dyadic Quincunx Subsampling

We construct directional wavelet systems that will enable building efficient signal representation schemes with good direction selectivity. In particular, we focus on wavelet bases with dyadic quincunx subsampling. In our previous work (Yin, in: Proceedings of the 2015 international conference on sampling theory and applications (SampTA), 2015), we show that the supports of orthonormal wavelets in our framework are discontinuous in the frequency domain, yet this irregularity constraint can be avoided in frames, even with redundancy factor <2. In this paper, we focus on the extension of orthonormal wavelets to biorthogonal wavelets and show that the same obstruction of regularity as in orthonormal schemes exists in biorthogonal schemes. In addition, we provide a numerical algorithm for biorthogonal wavelets construction where the dual wavelets can be optimized, though at the cost of deteriorating the primal wavelets due to the intrinsic irregularity of biorthogonal schemes.     

Orthogonal Helmholtz decomposition in arbitrary dimension using divergence-free and curl-free wavelets

We present tensor-product divergence-free and curl-free wavelets, and define associated projectors. These projectors enable the construction of an iterative algorithm to compute the Helmholtz decomposition of any vector field, in wavelet domain. This decomposition is localized in space, in contrast to the Helmholtz decomposition calculated by Fourier transform. Then we prove the convergence of the algorithm in dimension two for any kind of wavelets, and in larger dimension for the particular case of Shannon wavelets. We also present a modification of the algorithm by using quasi-isotropic divergence-free and curl-free wavelets. Finally, numerical tests show the validity of this approach for a large class of wavelets.     

Construction of Periodic Prolate Spheroidal Wavelets Using Interpolation

Periodic prolate spheroidal wavelets (periodic PS wavelets), based on the periodizaton of the first prolate spheroidal wave function (PSWF), were recently introduced by the authors. Because of localization and other properties, these periodic PS wavelets could serve as an alternative to Fourier series for applications in modeling periodic signals. In this paper, we continue our work with periodic PS wavelets and direct our attention to their construction via interpolation. We show that they have a representation in terms of interpolation with the modified Dirichlet kernel. We then derive a group of formulas of interpolation type based on this representation. These formulas enable one to obtain a simple procedure for the calculation of the periodic PS wavelets and finding expansion coefficients. In particular, they are used to compute filter coefficients for the periodic PS wavelets. This is done for a number of concrete cases.